Total 53,674 skills, AI & Machine Learning has 8931 skills
Showing 12 of 8931 skills
Cross-tool AI consultation. Use when user asks to 'consult gemini', 'ask codex', 'get second opinion', 'cross-check with claude', 'consult another AI', 'ask opencode', 'copilot opinion', or wants a second opinion from a different AI tool.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.
Analyze the overall sentiment and tone of management during earnings conference calls, including confidence levels, optimism indicators, and forward-looking language.
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.
Fully autonomous research pipeline that turns a topic idea into a complete academic paper with real citations, experiments, and conference-ready LaTeX.
Spawn 10 independent parallel agents to analyze source material from distinct perspectives, synthesize findings, and apply improvements to a target agent or skill. Use when source material is complex and multi-angle extraction justifies 3-5x token cost over inline analysis. Use for "parallel analysis", "multi-perspective", or "deep extraction". Do NOT use for routine improvements, simple source material, or when token budget is limited.
Agent skill for orchestrator-task - invoke with $agent-orchestrator-task
Operates AIR agentic wallets through AIR's `/v2/wallet/agent-sign` HTTP endpoint and ERC-4337 UserOps. Use when an external agent receives an AIR handoff bundle with `userId`, `walletId`, `privyAppId`, `abstractAccountAddress`, and `airApiAgentSignUrl`, and needs to sign messages, typed data, or control the smart account onchain.
Use these skills to set up and optimize production-ready vector workloads by simply expressing your intent and performance requirements.
Autonomous project gardening by a coordinated team of agents. Spawns a team of gardeners that each run the `garden` skill in parallel, coordinating via a shared task list to avoid duplicate work. Use when the user wants to tend multiple small issues in one pass. Invoke with /gardeners.
Expert in physical and human geography, climate systems, cartography, and spatial analysis — builds geographically coherent worlds where terrain, climate, resources, and settlement patterns make scientific sense